Liveness Detection for Embedded Face Recognition System
To increase reliability of face recognition system, the
system must be able to distinguish real face from a copy of face such
as a photograph. In this paper, we propose a fast and memory efficient
method of live face detection for embedded face recognition system,
based on the analysis of the movement of the eyes. We detect eyes in
sequential input images and calculate variation of each eye region to
determine whether the input face is a real face or not. Experimental
results show that the proposed approach is competitive and promising
for live face detection.
[1] N. K. Ratha, J. H. Connell, and R. M. Bolle, "Enhancing security and
privacy in biometrics-based authentication systems," IBM Systems
Journal, vol. 40, no. 2, pp. 614-634, 1995.
[2] Stephanie A. C. Schuckers, "Spoofing and anti-spoofing measures,"
Information Security Technical Report, Vol. 7, no. 4, pp. 56-62, 2002.
[3] T. Choudhury, B. Clarkson, T. Jebara, and A. Pentland, "Multimodal
person recognition using unconstrained audio and video," International
Conference on AVBPA, pp. 22-28, 1999.
[4] J. K. Aggarwal, N. Nandhakumar, "On the Computation of Motion from
Sequences of Images - A Review," Proc. IEEE, vol. 76, pp. 917-935,
1998.
[5] J. Li, Y. Wang, T. Tan, and A. K. Jain, "Live face detection based on the
analysis of fourier spectra," In Biometric Technology for Human
Identification, SPIE vol. 5404, pp. 296-303, 2004.
[6] R. O. Duda, P. E. Hart, D. G. Stork, "Pattern Classification," 2nd eds, A
Wiley-Interscience Publication, 2001.
[7] P. Viola and M. Jones, "Rapid Object Detection using a Boosted Cascade
of Simple Features," In Proceedings of IEEE International Conference on
Computer Vision and Pattern Recognition, pp. 511-518, 2001.
[8] H. Wang, S. Z. Li, Y. Wang, "Face Recognition under Varying Lighting
Condition Using Self Quotient Image," In Proceedings of International
Conference on Automatic Face and Gesture Recognition, pp. 819-824,
2004.
[9] W. Zhao, R. Chellappa A. Rosenfeld, P. J. Phillips, "Face Recognition: A
Literature Survey," Technical Reports of Computer Vision Laboratory of
University of Maryland, 2000.
[1] N. K. Ratha, J. H. Connell, and R. M. Bolle, "Enhancing security and
privacy in biometrics-based authentication systems," IBM Systems
Journal, vol. 40, no. 2, pp. 614-634, 1995.
[2] Stephanie A. C. Schuckers, "Spoofing and anti-spoofing measures,"
Information Security Technical Report, Vol. 7, no. 4, pp. 56-62, 2002.
[3] T. Choudhury, B. Clarkson, T. Jebara, and A. Pentland, "Multimodal
person recognition using unconstrained audio and video," International
Conference on AVBPA, pp. 22-28, 1999.
[4] J. K. Aggarwal, N. Nandhakumar, "On the Computation of Motion from
Sequences of Images - A Review," Proc. IEEE, vol. 76, pp. 917-935,
1998.
[5] J. Li, Y. Wang, T. Tan, and A. K. Jain, "Live face detection based on the
analysis of fourier spectra," In Biometric Technology for Human
Identification, SPIE vol. 5404, pp. 296-303, 2004.
[6] R. O. Duda, P. E. Hart, D. G. Stork, "Pattern Classification," 2nd eds, A
Wiley-Interscience Publication, 2001.
[7] P. Viola and M. Jones, "Rapid Object Detection using a Boosted Cascade
of Simple Features," In Proceedings of IEEE International Conference on
Computer Vision and Pattern Recognition, pp. 511-518, 2001.
[8] H. Wang, S. Z. Li, Y. Wang, "Face Recognition under Varying Lighting
Condition Using Self Quotient Image," In Proceedings of International
Conference on Automatic Face and Gesture Recognition, pp. 819-824,
2004.
[9] W. Zhao, R. Chellappa A. Rosenfeld, P. J. Phillips, "Face Recognition: A
Literature Survey," Technical Reports of Computer Vision Laboratory of
University of Maryland, 2000.
@article{"International Journal of Information, Control and Computer Sciences:54404", author = "Hyung-Keun Jee and Sung-Uk Jung and Jang-Hee Yoo", title = "Liveness Detection for Embedded Face Recognition System", abstract = "To increase reliability of face recognition system, the
system must be able to distinguish real face from a copy of face such
as a photograph. In this paper, we propose a fast and memory efficient
method of live face detection for embedded face recognition system,
based on the analysis of the movement of the eyes. We detect eyes in
sequential input images and calculate variation of each eye region to
determine whether the input face is a real face or not. Experimental
results show that the proposed approach is competitive and promising
for live face detection.", keywords = "Liveness Detection, Eye detection, SQI.", volume = "2", number = "6", pages = "1944-4", }